所提出计算模型为贝叶斯网的概率推理提供了一种新的局部计算方法。
The proposed computation models will supply new local computation methods for Bayesian network probabilistic inferences.
该文就是基于这个思想提出了新的人脸识别算法，即加强概率推理模型。
This paper proposes a new algorithm to boost performance of probabilistic reasoning model(PRM) face recognition methods.
因果图理论是可以进行故障分析的概率推理方法，但是缺乏对故障模式的重要性的分析。
Causality diagram methodology is a probabilistic reasoning, which can be applied to fault analysis. However, it lacks analysis on the importance of failure mode.
同时利用贝叶斯网络实现概率推理，便于描述故障特征的变化及对变压器故障原因的快速分析。
At the same time, probability reasoning can be realized by BN, which can be used to describe changes of fault symptoms and analyze fault reasons of transformer.
而已知的是，人们是通过在脑中不断地计算和修正概率来做出决定的，这被叫做“概率推理”。
What is known is that people make decisions based on probabilities that are constantly being calculated and refined in their heads—something called "probabilistic inference".
本文在向量空间模型和概率推理网络的基础上提出了一个基于关键词与概念相结合的混合信息检索模型。
We bring forward a hybrid model that is based on a combination of keywords and concept. The hybrid model is built on vector space model and probabilistic reasoning network.
巴韦利埃指出，在诡异的后启示录世界消灭从任意方向展开攻击的敌人能够提高经验丰富的游戏玩家的概率推理能力。
Those who get a lot of practice, say, killing zombies attacking from haphazard directions in a shifting, postapocalyptic landscape pump up their probabilistic inference powers, Bavelier proposes.
贝叶斯网络是在不确定性环境下有效的知识表示方式和概率推理模型，是一种流行的图形决策化分析工具。
Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
将模糊数学、概率推理和节约覆盖集理论引入到汽车故障诊断中，建立了一个新的汽车故障综合诊断模型。
The new auto malfunction diagnosis model is based on the fuzzy theory, probability reasoning and parsimonious covering theory.
本文利用不确定推理中的概率推理方法，设计了购买决策树回溯推理的模型和算法，有效解决了这一问题。
Using uncertain reasoning, a reasoning model and an algorithm are presented, which give the answer to this problem effectively.
贝叶斯网络是数据采掘的一个非常有效的工具，它能够定性和定量地分析属性之间的依赖关系，进行概率推理。
Bayesian network as, a very useful tool in data mining, can provide qualitative and quantitative relationship between attributes and probability inference.
然而，我们知道的是，人们做出的决定基于对概率的判断，而此他们在头脑中不断计算和精确这个判断——这叫做“概率推理”。
What is known, however, is that people make decisions based on probabilities, which are constantly being calculated and refined in their heads—something called “probabilistic inference”.
本文主要涉及的不确定推理模型包括主观贝叶斯的概率推理模型，可信度理论推理模型，证据理论及其改进推理模型以及神经网络推理模型。
In the paper, the models of uncertain reasoning are focused, such as the reasoning model of Bayes probability, Reliability theory, D-S evidence theory and Neural Network.
巴韦利埃表示：“令人感到吃惊的是，靠玩动作游戏提高的概率推理能力并不仅限于游戏，同时也可用于完成与游戏无关的更为鼓噪的任务。”
“What’s surprising in our study is that action games improved probabilistic inference not just for the act of gaming, but for unrelated and rather dull tasks,” Bavelier says.
其中一条关于试图回答休谟理论的便是，归纳法实际上可以经由纯粹的推理证明，而不是演示，诉之于概率的除外。
One way of trying to answer Hume is to show that actually induction can be justified by pure reason but by appeal to probability rather than demonstration.
此类关于概率感知假设的契合点洛克已经思考过了,认为人类推理的基础原来只是视觉思维。
The sort of supposed perception of probable connections that Locke had thought was the basis of human reasoning turns out to be visual thinking.
当我们推理概率或者道德推理的时候，根据洛克的理论我们从过去的经验中发现证据推理的契合，但那只是概率的连接并不是演示的契合。
In probable or moral reasoning when we reason, uh from past experience according to Locke we see evidential connections but there are only probable connections not uh, demonstrative ones.
在分析多个理论模型的基础上，采用贝叶斯定理证明了前提概率原则，并将此原则与人类心理过程相结合，将归纳推理分解为连续进行的三步过程。
After analyzing several theory models of inductive reasoning, we use the Bayes Theorem to prove the premise probability principle, and integrate this theory with human mental process.
他还将概率逻辑思想应用于归纳推理合理性的辩护之中，在概率逻辑的基础之上建立了他的辩护理论。
He also justified induction by means of his logic thoughts, and constructed his justification of induction on the basis of his probability logic theory.
目的：介绍条件推理领域心理模型理论与概率理论以及它们之间的争论与融合。
OBJECTIVE: To introduce the mental model theory and probabilistic theory with their disputation and tradeoff in conditional inference domain.
推理机制的量化是通过引入概率信息实现的。
The reasoning mechanism is quantified by introducing information of probability.
启发式概率估计是当前国外自然推理研究的新兴的热点问题之一。
Heuristic probability estimate is one of the popular issue of natural reasoning in foreign psychological research currently.
重点介绍概率理论的历史，以及盖然论和因果推理的计算方法。
Emphasizes history of probability theory and computational approaches to probabilistic and causal inference.
利用概率时间网络，对完备相互排他过程进行时间推理，并以一个具体的实例，对此过程进行了说明。
This paper fulfills temporal reasoning for the exhaustive and exclusive process by using the probabilistic temporal network, and shows the process by a real-world example.
基于语言交际中推理的有效性具有某种概率性，本文提出日常推理不只依赖于逻辑。
Considering some inferences that are valid with a certain degree of probability in linguistic communication, the paper tries to argue that everyday reasoning depends on more than logic.
在控制系统中，将贝叶斯概率引入到模糊rbf神经网络中，增强了系统的推理能力，提高了飞机各个航道位置的模拟伺服精度。
In the control system, Bayes probability is introduced in the fuzzy RBF neural network and it intensity the inference ability and increase the servo precision.
该推理模型前级采用神经网络并行子网，用于目标的预分类，后级采用证据理论用于多周期的不确定性推理和概率的全局分配。
The forestage of the fusion model completes target presort and its post-stage is used to multi-period uncertainty inference and the whole set distribution of probability.
该推理模型前级采用神经网络并行子网，用于目标的预分类，后级采用证据理论用于多周期的不确定性推理和概率的全局分配。
The forestage of the fusion model completes target presort and its post-stage is used to multi-period uncertainty inference and the whole set distribution of probability.
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